5 Sales Analytics that help Auditors to Make Real Savings
The audit team is not always the most popular visitor to a department. After all, who likes to be checked up on and told which activities have not been carried out properly? Often topics such as the internal system of control and the compliance of employees within the department are seen as a bureaucratic obstacle. In today’s blog post, I would like to present 5 data indicators for sales audits, which are closely related to your company’s liquidity. If you, as an auditor, can make findings that can be “calculated” directly in € or $, you won’t need to explain the value of your work to anyone!
In the last blog post, “9 Sales Data Analytics that Every Auditor should be Aware of“, I already presented the 9 important data indicators for a sales audit. In what follows, I will present 5 data indicators related to “cash” savings.
Data indicator 1: Customers without credit limit
A credit limit prevents customers from accumulating too many receivables. There is a risk that customer invoices will not be settled because they are being processed without credit limits and the customer may in some cases be being over-supplied. Not every organization works with credit limits. A data analysis should therefore use other criteria to find critical evidence. A data analysis can thus be used to find such evidence in the following way: A document will be marked if it is a customer invoice (item in debit with account type customer) and (A) no direct debit authorization has been granted, (B) no credit limit has been defined, and c) the customer has never paid anything in the fiscal year under review, or the customer has been warned, or the customer has paid later than double the length of the payment terms.
Data indicator 2: Reversed accounts receivables
It is rather unusual to see outgoing invoices that are canceled very late after posting. One possible “pattern of fraud” is to cancel outgoing invoices, because otherwise they have to be corrected individually. They are then re-entered instead. The outgoing invoices then once again become “freshly” issued and so are not yet immediately due once again. There is thus a risk that receivables that ought to be depreciated are being canceled (late) and re-entered again in order to avoid depreciation. This can be determined by a data analysis in the following way: The document is marked if it has a debit item in debit (= claim) and this document has been canceled more than 30 days after its posting date. It is also relevant how many accounts receivable documents from customers have been registered within 14 days after the date of the cancellation.
Data indicator 3: Customer paid after payment term
Not all customers have the highest moral standards when it comes to paying on time. As an auditor, you should be able to find out when claims are taking or have taken too long to be settled, as there is the risk of late payments and liquidity bottlenecks, as well as losses of interest. A data analysis can be carried out based on the following criteria: A document is marked if the customer only pays three days or more after the end of the payment period.
Data indicator 4: Indications for duplicate paid credit notes
Normally, the money comes in during the sales process purely and then does not go out again. However, there may also be outgoing cash flows in the sales process, e.g. when credits are paid out. There is therefore the risk that credits may be paid out or balanced several times because e.g. they have been entered several times (accidentally). Using data analysis, such a phenomenon can be identified as follows: The document is marked if it contains a credit note that has been balanced or offset by means of an (outgoing) payment, where there are further items from other credit notes (and/or with respect to the same customer), which have also been paid out or offset for the same amount.
Data indicator 5: Missing or inappropriate payment terms on sales invoices
Frequently, customers do not pay your invoices in time. What is even worse is when you find out that you are also a little to blame for the situation yourself. This might be the case if you do not have any payment terms at all or if you have terms of payment that are poorly maintained. There is then the risk of late receipt of payments. A data analysis can be used to evaluate the situation based on the following criteria: An outgoing invoice is marked if the document contains no or incomplete payment conditions. The fields in the document for calculating the cash discount periods are not maintained even though the cash discount has been defined in the document (which is obviously not sufficient due to the lack of a discount period). Documents which have no reference to a payment condition at all should also be taken into account. Invoices to affiliated companies are usually not of much interest here and can be filtered out.
In addition to the 5 sales data indicators presented here, there are many other data indicators available! If you want to find out more about what you can analyze for the purposes of your next sales audit, you can download a description of all the sales data indicators available in zapliance here: